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References from Clinician Trust and Human Factors in AI-Enabled Clinical Decision Support in Acute Care: Mixed Methods Study. Local targets link to admitted publications; unresolved targets remain external evidence.
AI-driven clinical decision support systems: an ongoing pursuit of potential
10.7759/cureus.57728 · External reference
Achieving large-scale clinician adoption of AI-enabled decision support
10.1136/bmjhci-2023-100971 · External reference
A new sociotechnical model for studying health information technology in complex adaptive healthcare systems
10.1136/qshc.2010.042085 · External reference
An overview of clinical decision support systems: benefits, risks, and strategies for success
10.1038/s41746-020-0221-y · External reference
Interruptive versus noninterruptive clinical decision support: usability study
10.2196/12469 · External reference
The Precision Resuscitation With Crystalloids in Sepsis (PRECISE) trial: a trial protocol
10.1001/jamanetworkopen.2024.34197 · External reference
A roadmap for national action on clinical decision support
10.1197/jamia.m2334 · External reference
Trust in artificial intelligence-based clinical decision support systems among health care workers: systematic review
10.2196/69678 · External reference
Human-centered artificial intelligence: reliable, safe & trustworthy
10.1080/10447318.2020.1741118 · External reference
SEIPS 2.0: a human factors framework for studying and improving the work of healthcare professionals and patients
10.1080/00140139.2013.838643 · External reference
Perceived usefulness, perceived ease of use, and user acceptance of information technology
10.2307/249008 · External reference
Foundations for an empirically determined scale of trust in automated systems
10.1207/s15327566ijce0401_04 · External reference
Trust in automation: integrating empirical evidence on factors that influence trust
10.1177/0018720814547570 · External reference
The quality of mixed methods studies in health services research
10.1258/jhsrp.2007.007074 · External reference
Improving the quality of web surveys: the Checklist for Reporting Results of Internet E-Surveys (CHERRIES)
10.2196/jmir.6.3.e34 · External reference
User acceptance of information technology: toward a unified view
10.2307/30036540 · External reference
Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups
10.1093/intqhc/mzm042 · External reference
From alpha to omega: a practical solution to the pervasive problem of internal consistency estimation
10.1111/bjop.12046 · External reference
Using thematic analysis in psychology
10.1191/1478088706qp063oa · External reference
Sample size in qualitative interview studies: guided by information power
10.1177/1049732315617444 · External reference
Code saturation versus meaning saturation: how many interviews are enough?
10.1177/1049732316665344 · External reference
Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
10.1038/s41591-022-01772-9 · External reference
How explainable artificial intelligence can increase or decrease clinicians’ trust in AI applications in health care: systematic review
10.2196/53207 · External reference
Electronic diagnostic support in emergency physician triage: qualitative study with thematic analysis of interviews
10.2196/39234 · External reference
Trust and stakeholder perspectives on the implementation of AI tools in clinical radiology
10.1007/s00330-023-09967-5 · External reference
Explainability for artificial intelligence in healthcare: a multidisciplinary perspective
10.1186/s12911-020-01332-6 · External reference
“Hello AI”: uncovering the onboarding needs of medical practitioners for human-AI collaborative decision-making
10.1145/3359206 · External reference
Roles and competencies of doctors in artificial intelligence implementation: qualitative analysis through physician interviews
10.2196/46020 · External reference
Evaluating the prevalence of burnout among health care professionals related to electronic health record use: systematic review and meta-analysis
10.2196/54811 · External reference
Integrating the practical robust implementation and sustainability model with best practices in clinical decision support design: implementation science approach
10.2196/19676 · External reference
Attitudes towards artificial intelligence in emergency medicine
10.1111/1742-6723.14345 · External reference
Successful implementation of an artificial intelligence-based computer-aided detection system for chest radiography in daily clinical practice
10.3348/kjr.2022.0193 · External reference
Hospital-wide survey of clinical experience with artificial intelligence applied to daily chest radiographs
10.1371/journal.pone.0282123 · External reference
Towards human-AI collaboration in radiology: a multidimensional evaluation of the acceptability of AI for chest radiograph analysis in supporting pulmonary tuberculosis diagnosis
10.1093/jamiaopen/ooae151 · External reference
Evaluation of an artificial intelligence model for detection of pneumothorax and tension pneumothorax in chest radiographs
10.1001/jamanetworkopen.2022.47172 · External reference
Innovative strategies against superbugs: developing an AI-CDSS for precise Stenotrophomonas maltophilia treatment
10.1016/j.jgar.2024.06.004 · External reference
Conceptualizing clinicians’ trust in artificial intelligence as a function of their expertise, workload, patient outcome, diagnosis difficulty, and AI accuracy: a systems thinking approach
10.1109/access.2025.3586555 · External reference
A comprehensive overview of barriers and strategies for AI implementation in healthcare: mixed-method design
10.1371/journal.pone.0305949 · External reference
Barriers to and facilitators of clinician acceptance and use of artificial intelligence in healthcare settings: a scoping review
10.1136/bmjopen-2024-092624 · External reference
Competencies for the use of artificial intelligence-based tools by health care professionals
10.1097/acm.0000000000004963 · External reference
Electronic health record data quality assessment and tools: a systematic review
10.1093/jamia/ocad120 · External reference
Enhancing AI clinical decision support trust: design workshop insights from general practitioners
10.3233/shti250909 · External reference
Applying requisite imagination to safeguard electronic health record transitions
10.1093/jamia/ocab291 · External reference
Balancing act: the complex role of artificial intelligence in addressing burnout and healthcare workforce dynamics
10.1136/bmjhci-2024-101120 · External reference
Patient perspectives on the use of artificial intelligence in health care: a scoping review
10.17294/2330-0698.2029 · External reference
SEIPS 3.0: Human-centered design of the patient journey for patient safety
10.1016/j.apergo.2019.103033 · External reference